Scheduling method and apparatus for control average transmission rate in multiple antenna system

ABSTRACT

A scheduling method in a wireless communication includes receiving a Channel Quality Indicator (CQI) from a plurality of terminals. The method also includes determining an average transmission rate of each terminal based on the CQI by approximating an instantaneous transmission rate distribution to a Gaussian distribution. The method further includes determining a weight of each terminal such that the average transmission rate of each terminal satisfies a target transmission rate. The method also includes selecting a terminal set by applying the determined weight. Thus, it is possible to control the fairness between the terminals and to efficiently control the transmission rate of the terminals according to the required transmission rate and the channel environment of the terminals.

CROSS-REFERENCE TO RELATED APPLICATION(S) AND CLAIM OF PRIORITY

The present application is related to and claims priority under 35U.S.C. §119 to a Korean patent application filed in the KoreanIntellectual Property Office on Aug. 2, 2010, and assigned Serial No.10-2010-0074691, the contents of which is herein incorporated byreference.

TECHNICAL FIELD OF THE INVENTION

The present invention relates generally to a scheduling apparatus andmethod for controlling fairness between terminals and an averagetransmission rate of each terminal in a downlink wireless communicationsystem including multiple-input multiple-output antennas.

BACKGROUND OF THE INVENTION

Recently, demand for wireless communication service is increasing, whichleads to a request to increase wireless communication system capacity.To increase the wireless communication system capacity, Multiple-InputMultiple-Output (MIMO) technology and scheduling technology for managingradio resources are suggested and developed.

Spatial Multiplexing (SM) and Space Division Multiple Access (SDMA)techniques are suggested as the representative of the MIMO technology,and standardized by 3^(rd) Generation Partnership Project (3GPP) LongTerm Evolution (LTE) and Mobile WiMAX. The SDMA technique increases thesystem capacity by concurrently sending a data stream to plurality ofterminals per cell. Accordingly, how a base station effectively selectsterminals to send the data at the same time from all of terminalsrequesting to send the data (that is, a scheduling method) greatlyaffects a system capacity gain according to the SDMA technique. Thus,the MIMO technology, particularly, the SDMA technique should be jointlyoptimized with the scheduling technique.

The scheduling technique in the wireless communication system enablesthe base station to select a terminal to send the data among theterminals requesting the data transmission. The scheduling should bedesigned to maintain fairness between the terminals in terms of the datatransmission rate and to increase the system capacity.

A representative scheduling algorithm adopted in the wirelesscommunication system is a Proportional Fair (PF) scheduling algorithm.The PF scheduling algorithm allows the terminal having the greatestratio of an instantaneous transmission rate to an average transmissionrate to send data using an instantaneous transmission rate informationof each terminal fed back to the base station. Hence, since the data istransmitted to the terminal with the best instantaneous channel statecompared to the average channel state, the system transmission capacityis raised and all of the terminals are given the transmissionopportunity in the same number of times. As all of the terminals aregiven the transmission opportunity in the same number of times, theaverage transmission rate of each terminal is proportional to theaverage channel state of the corresponding terminal, which is referredto as proportional fairness between the terminals.

However, a PF scheduler, which ensures merely the proportional fairnessbetween the terminals, cannot ensure a minimum required transmissionrate for the service with respect to the terminals having low averagereceived Signal to Interference and Noise Ratio (SINR). Further, the PFscheduler can offer the transmission opportunity over a maximum requiredtransmission rate for the service to the terminals having a very goodchannel state.

In conclusion, in the downlink wireless communication system includingMIMO antennas, a scheduling method and a scheduling apparatus are neededto control the fairness between the terminals and to control thetransmission rate of the terminals according to the requiredtransmission rate and the channel condition of the terminals.

SUMMARY OF THE INVENTION

To address the above-discussed deficiencies of the prior art, it is aprimary aspect of the present invention to solve at least theabove-mentioned problems and/or disadvantages and to provide at leastthe advantages described below. Accordingly, an aspect of the presentinvention is to provide a scheduling method and a scheduling apparatusfor controlling an average transmission rate of a terminal in a multipleantenna system.

Another aspect of the present invention is to provide a schedulingmethod and a scheduling apparatus for controlling fairness betweenterminals and controlling a transmission rate of the terminals accordingto a required transmission rate and channel environment of the terminalsin a downlink wireless communication system including MIMO antennas.

According to one aspect of the present invention, a scheduling method ina wireless communication includes receiving a Channel Quality Indicator(CQI) from a plurality of terminals. The method also includesdetermining an average transmission rate of each terminal based on theCQI by approximating an instantaneous transmission rate distribution toa Gaussian distribution. The method further includes determining aweight of each terminal such that the average transmission rate of eachterminal satisfies a target transmission rate. The method also includesselecting a terminal set by applying the determined weight.

According to another aspect of the present invention, a schedulingapparatus in a wireless communication includes a receiver configured toreceive a CQI from a plurality of terminals. The scheduling apparatusalso includes an average transmission rate determiner configured todetermine an average transmission rate of each terminal based on the CQIby approximating an instantaneous transmission rate distribution to aGaussian distribution. The scheduling apparatus also includes an averagetransmission rate controller configured to determine a weight of eachterminal such that the average transmission rate of each terminalsatisfies a target transmission rate. The scheduling apparatus alsoincludes a terminal selector configured to select a terminal set byapplying the determined weight.

Before undertaking the DETAILED DESCRIPTION OF THE INVENTION below, itmay be advantageous to set forth definitions of certain words andphrases used throughout this patent document: the terms “include” and“comprise,” as well as derivatives thereof, mean inclusion withoutlimitation; the term “or,” is inclusive, meaning and/or; the phrases“associated with” and “associated therewith,” as well as derivativesthereof, may mean to include, be included within, interconnect with,contain, be contained within, connect to or with, couple to or with, becommunicable with, cooperate with, interleave, juxtapose, be proximateto, be bound to or with, have, have a property of, or the like; and theterm “controller” means any device, system or part thereof that controlsat least one operation, such a device may be implemented in hardware,firmware or software, or some combination of at least two of the same.It should be noted that the functionality associated with any particularcontroller may be centralized or distributed, whether locally orremotely. Definitions for certain words and phrases are providedthroughout this patent document, those of ordinary skill in the artshould understand that in many, if not most instances, such definitionsapply to prior, as well as future uses of such defined words andphrases.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present disclosure and itsadvantages, reference is now made to the following description taken inconjunction with the accompanying drawings, in which like referencenumerals represent like parts:

FIG. 1 illustrates a generalized PF scheduler according to an embodimentof the present invention;

FIG. 2 is a table of a value ε(K) based on a value K according to anembodiment of the present invention;

FIG. 3 illustrates a terminal average transmission rate estimationalgorithm according to an embodiment of the present invention;

FIG. 4 illustrates a terminal average transmission rate controlalgorithm according to an embodiment of the present invention; and

FIG. 5 is a graph of simulation results.

DETAILED DESCRIPTION OF THE INVENTION

FIGS. 1 through 5, discussed below, and the various embodiments used todescribe the principles of the present disclosure in this patentdocument are by way of illustration only and should not be construed inany way to limit the scope of the disclosure. Those skilled in the artwill understand that the principles of the present disclosure may beimplemented in any suitably arranged communication system.

Preferred embodiments of the present invention will be described hereinbelow with reference to the accompanying drawings. In the followingdescription, well-known functions or constructions are not described indetail since they would obscure the invention in unnecessary detail.Terms described below, which are defined considering functions in thepresent invention, may be different depending on user and operator'sintention or practice. Therefore, the terms should be defined on thebasis of the disclosure throughout this specification.

Exemplary embodiments of the present invention provide a schedulingapparatus and a scheduling method for controlling fairness between usersand an average transmission rate of each user in a downlink wirelesscommunication system including Multiple-Input Multiple-Output (MIMO)antennas.

Generalized Proportional Fair (PF) Scheduling Algorithm

In a downlink cellular network, K-ary terminals wanting to receivedownlink data estimate their downlink channel and calculate a maximumtransmission rate for sending data over the corresponding link. Eachterminal feeds the calculated maximum transmission rate information backto a base station over a reverse link channel. Using the maximumtransmission rate information fed back from each terminal, a basestation scheduler determines a terminal to service in a next downlinktime slot according to a given scheduling algorithm.

A PF scheduling algorithm, which is a representative schedulingalgorithm, selects a terminal set O_(S)[n] to optimize a utilityfunction f_(i)(R_(i)[n])=log(R_(i)[n]) given by Equation 1.

$\begin{matrix}\begin{matrix}{{O_{S}\lbrack n\rbrack} = {\underset{O}{\arg \; \max}\left( {\sum\limits_{i \in O}{f_{i}\left( {R_{i}\lbrack n\rbrack} \right)}} \right)}} \\{= {\underset{O}{\arg \; \max}\left( {\sum\limits_{i \in O}{\log \left( {R_{i}\lbrack n\rbrack} \right)}} \right)}}\end{matrix} & \left\lbrack {{Eqn}.\mspace{14mu} 1} \right\rbrack\end{matrix}$

In Equation 1, O denotes all feasible subsets for the K-ary terminalswanting the data transmission, and O_(S)[n] denotes a terminal setselected by a scheduler S to service in the n-th time slot. R_(i)[n]denotes an average transmission rate of the i-th terminal and is givenby Equation 2.

$\begin{matrix}{{R_{i}\lbrack n\rbrack} = \left\{ \begin{matrix}{{{\frac{T - 1}{T}{R_{i}\left\lbrack {n - 1} \right\rbrack}} + {\frac{1}{T}{r_{i}\lbrack n\rbrack}}},} & {{{if}\mspace{14mu} i} \in {O_{S}\lbrack n\rbrack}} \\{{\frac{T - 1}{T}{R_{i}\left\lbrack {n - 1} \right\rbrack}},} & {otherwise}\end{matrix} \right.} & \left\lbrack {{Eqn}.\mspace{14mu} 2} \right\rbrack\end{matrix}$

In Equation 2, r_(i)[n] denotes an instantaneous transmission rate ofthe i-th terminal transmittable in the n-th time slot, and T denotes atime constant for calculating an exponential moving average. Based onEquation 1, the PF scheduling algorithm selects the terminal subsetwhich maximizes the sum of the log value of the average transmissionrate of the terminal. That is, the PF scheduling algorithm calculatesthe log sum of the average transmission rate of the terminals belongingto the subsets O of every possible terminal, selects one subset of themaximum log sum, and transmits data to the terminals belonging to theselected subset.

However, rather than applying the utility function optimizationalgorithm of Equation 1 to the actual system, the PF schedulingalgorithm converts to and implements an optimization algorithm forselecting the terminal set which maximizes the sum of the ratio of theinstantaneous transmission rate to the average transmission rate asexpressed in Equation 3.

$\begin{matrix}{{O_{S}\lbrack n\rbrack} = {\underset{O}{argmax}{\sum\limits_{i \in O}\frac{r_{i}\lbrack n\rbrack}{R_{i}\left\lbrack {n - 1} \right\rbrack}}}} & \left\lbrack {{Eqn}.\mspace{14mu} 3} \right\rbrack\end{matrix}$

The calculation of Equation 3 is simpler than the calculation ofEquation 1, and Equation 3 provides a physical understanding about thescheduling algorithm operation which schedules the terminals having agreater instantaneous transmission rate than the average transmissionrate and allows the theoretical capacity analysis. Hence, to apply tothe actual system, it is necessary to convert the optimization algorithmfor the utility function of Equation 1 to the optimization algorithm ofEquation 3 which is equivalent to but much simpler than Equation 1.

A conventional PF scheduling algorithm cannot regulate the fairnessdegree of the terminals, that is, the difference between the terminalaverage transmission rates. Also, the conventional PF schedulingalgorithm cannot individually regulate the average transmission rate ofthe terminal. To address those shortcomings, a generalized PF schedulingalgorithm is suggested. The generalized PF scheduling algorithm canregulate the fairness between the terminals using a parameter α, andindividually regulate the average transmission rate of the terminalsusing a priority parameter p_(i). The utility function of thegeneralized PF scheduler is given by Equation 4.

$\begin{matrix}{{f_{i}\left( {R_{i}\lbrack n\rbrack} \right)} = \left\{ \begin{matrix}{{p_{i}{\log \left( {R_{i}\lbrack n\rbrack} \right)}},} & {\alpha = 1} \\{{p_{i}\frac{\left( {R_{i}\lbrack n\rbrack} \right)^{1 - \alpha}}{1 - \alpha}},} & {otherwise}\end{matrix} \right.} & \left\lbrack {{Eqn}.\mspace{14mu} 4} \right\rbrack\end{matrix}$

In Equation 4, when α=1 and p_(i)=1 for every p_(i), the generalized PFscheduling algorithm is the same as the PF scheduling algorithm. As thevalue α increases, the difference between the average transmission ratesof the terminal reduces. The terminal having a greater p_(i) has moretransmission opportunity than a terminal having a smaller value. Hence,the average transmission rate of the terminal can be controlledindividually.

The present invention provides the generalized PF scheduling algorithmto apply to the actual system. While the suggested generalized PFscheduling algorithm is theoretically derived from the optimizationalgorithm for the utility function of Equation 4, its derivation isomitted. While the suggested generalized PF scheduling algorithm isequivalent to the optimization algorithm for the utility function ofEquation 4, its calculation is much simpler and allows the theoreticalcapacity analysis. Thus, the generalized PF scheduling of the presentinvention allows an average transmission rate prediction method and anaverage transmission rate control method of the terminal. The suggestedgeneralized PF scheduling of the present invention is given by Equation5.

$\begin{matrix}{{O_{S}\lbrack n\rbrack} = {\underset{O}{\arg \; \max}{\sum\limits_{i \in O}\left\{ {p_{i}\frac{r_{i}\lbrack n\rbrack}{\left( {R_{i}\left\lbrack {n - 1} \right\rbrack} \right)^{\alpha}}} \right\}}}} & \left\lbrack {{Eqn}.\mspace{14mu} 5} \right\rbrack\end{matrix}$

FIG. 1 illustrates a generalized PF scheduler according to an embodimentof the present invention.

Referring to FIG. 1, the scheduler 100 includes a Channel QualityIndicator (CQI) feedback information receiver 102, an averagetransmission rate estimator 104, an average transmission rate controller106, and a terminal selector 108. The scheduler 100 is included to thebase station and used to schedule downlink data.

The CQI feedback information receiver 102 receives CQI information fromeach terminal over an uplink feedback channel. The CQI informationrepresents one or more signal to noise ratios (e.g., Signal-to-NoiseRatio (SNR), Signal-to-Interference-plus-Noise-Ratio (SINR),Carrier-to-Noise-Ratio (CNR), orCarrier-to-Interference-plus-Noise-Ratio (CINR)) measured by theterminal, with a predetermined number of bits (e.g., five bits or fourbits).

The average transmission rate estimator 104 estimates the averagetransmission rate over a corresponding radio link based on the CQIinformation fed back from the terminals. The average transmission rateis estimated using an average transmission rate prediction method of theterminal which approximates and estimates the instantaneous transmissionrate distribution to Gaussian distribution.

The average transmission rate controller 106 determines the value α andthe value {p_(i)}_(i=1, . . . , K) of the generalized PF scheduler bycomparing the estimated average transmission rate of the terminal with atarget transmission rate of the terminal so that the averagetransmission rate of the terminal reaches the target transmission rate.This average transmission rate control is fulfilled by an averagetransmission rate control method of the terminal of the presentinvention, which is explained by referring to FIG. 4.

The terminal selector 108 calculates a solution of the optimizationalgorithm of Equation 5 to select the terminal set O_(S)[n] to servicein each time slot. That is, the terminal selector 108 calculates the sumof the log value of the average transmission rate of the terminal(Equation 5) for every feasible subset O of the terminal and selects onesubset having the maximum value as the solution. In so doing, theterminal selector 108 uses the value α and the value{p_(i)}_(i=1, . . . , K) of the generalized PF scheduler determined bythe average transmission rate controller 106.

Lastly, the base station transmits data to the terminals belonging tothe subset selected by the terminal selector 108.

Average Transmission Rate Prediction Method of the Terminal According tothe Generalized PF Scheduling

The generalized PF scheduler regulates the value α for controlling thefairness between the terminals and the value {p_(i)}_(i=1, . . . , K)for individually controlling the average transmission rate of eachterminal. For doing so, the generalized PF scheduler is able to predictthe average transmission rate receivable by the terminal according tothe given value α and value {p_(i)}_(i=1, . . . , K). The presentinvention provides a method for predicting the average transmission ratereceivable by each terminal according to the given value α and value{p_(i)}_(i=1, . . . , K), which is conducted by the average transmissionrate estimator 104 of FIG. 1. This method minimizes necessarycomputation to apply to the actual system through real-time operation.

In the system using the generalized PF scheduling algorithm, when thevalue a and the value {p_(i)}_(i=1, . . . , K) are given, the averagetransmission rate R_(i) receivable by the i-th terminal is calculatedusing Equation 6. While Equation 6 is theoretically derived, thederivation is omitted.

$\begin{matrix}{R_{i} = \frac{\left( {p_{i}x_{i}^{eff}} \right)^{1/\alpha}}{\sum\limits_{k = 1}^{K}\frac{\left( {p_{k}x_{k}^{eff}} \right)^{1/\alpha}}{x_{k}^{eff}}}} & \left\lbrack {{Eqn}.\mspace{14mu} 6} \right\rbrack\end{matrix}$

In Equation 6, x_(i) ^(eff) is calculated based on Equation 7.

x _(i) ^(eff) =m _(i)+ε_(i)σ_(i)  [Eqn. 7]

In Equation 7, an average and a standard deviation when theinstantaneous transmission rate distribution receivable by the i-thterminal is approximated to the Gaussian distribution are defined asm_(i) and σ_(i) respectively. ε_(i) is a real value determined accordingto the number of users.

That is, m_(i), σ_(i) and ε_(i) can be obtained by approximating theinstantaneous transmission rate fed back from each terminal to theGaussian distribution at the base station scheduler. ε_(i) of Equation 7can be calculated based on Equation 8.

ε_(i)≈ε(K)=K∫ _(x=0) ^(∞) xf _((0,1))(x)(F _((0,1))(x))^(K-1) dx  [Eqn.8]

In Equation 8, f_((0,1)) and F_((0,1)) denote a Probability DistributionFunction (PDF) and a Cumulative Distribution Function (CDF) of thestandard normal distribution. ε_(i) is approximated to ε(K) determinedby the number K of the terminals requesting to receive downlink data,and determined according to the value K as shown in FIG. 2. Hence, thebase station scheduler calculates and stores the value ε(K) in advanceaccording to the value K, refers to and uses the stored values in everyaverage transmission rate prediction of the terminal, and thus reducesthe real-time calculation used in the scheduling.

FIG. 3 is a flowchart of a terminal average transmission rate estimationalgorithm according to an embodiment of the present invention.

Referring to FIG. 3, the scheduler receives the CQI information of eachterminal over the uplink feedback channel in block 300.

In block 302, the scheduler converts the received CQI information of theterminal to the instantaneous transmission rate transmittable over thecorresponding radio link. Herein, the scheduler converts the CQI to theinstantaneous transmission rate by applying backoff to the CQI fed backfrom each terminal in every hour, and schedules by considering frameerror occurring in the transmission. The instantaneous transmission rateinformation converted in every time slot is stored for the Gaussiandistribution approximation.

In block 304, the scheduler approximates the distribution ofinstantaneous transmission rate samples stored for each terminal to theGaussian distribution, and determines the average and the standarddeviation as m_(i) and σ_(i) of Equation 7.

In block 306, the scheduler determines the value ε(K) according to thevalue K to ε_(i) of Equation 7 by referring to the table of FIG. 2, andcalculates x_(i) ^(eff)=m_(i)+ε_(i)σ_(i) of Equation 7 using thedetermined values m_(i) and σ_(i).

In block 308, the scheduler calculates the average transmission rateR_(i) of each terminal by applying the given values α and{p}_(i=1, . . . , K), and the calculated value x_(i) ^(eff) of eachterminal to Equation 6.

Average Transmission Rate Control Method of the Terminal in theGeneralized PF Scheduling

The present invention provides a method for determining the value α andthe value {p_(i)}_(i=1, . . . , K) of the generalized PF scheduler bycomparing the estimated average transmission rate of each terminal withthe target transmission rate of each terminal, which is to be fulfilledby the average transmission rate controller 106 of FIG. 1, so that theaverage transmission rate of each terminal reaches the targettransmission rate.

The value α in the generalized PF scheduler is used to control thefairness between the terminals. A maximum throughput scheduling isimplemented when α=0, a proportional fair scheduling is implemented whenα=1, and a maxi-min scheduling is implemented when α=∞. Since the valueα affects the average transmission rate of the terminal, it cannot bechanged to a new value in every scheduling cycle. Thus, the fairnessdegree used in the wireless network is defined and the value α isspecified in accordance with the fairness degree.

To determine the value α, for example, when an initial weight value{p_(i)}_(i=1, . . . , K) for each terminal is given, the value α forsatisfying the system transmission rate (the total sum of the terminalaverage transmission rates

$\left. {\sum\limits_{i = 1}^{K}R_{i}} \right)$

with a desired value R^(sum) and satisfying the maximum fairness can beobtained from Equation 9.

$\begin{matrix}{R^{sum} = {\sum\limits_{i = 1}^{K}{\left( {p_{i}x_{i}^{eff}} \right)^{1/\alpha}/{\sum\limits_{k = 1}^{K}\frac{\left( {p_{k}x_{k}^{eff}} \right)^{1/\alpha}}{x_{k}^{eff}}}}}} & \left\lbrack {{Eqn}.\mspace{14mu} 9} \right\rbrack\end{matrix}$

When the initial weight value {p_(i)}_(i=1, . . . , K), the averagetransmission rate {x_(i) ^(eff)}_(i=1, . . . , K) receivable by eachterminal and predicted by the terminal average transmission rateestimation algorithm of FIG. 3, the target system transmission rateR^(sum), the value α satisfying Equation 9 (satisfying the maximumfairness) can be determined. In so doing, the target system transmissionrate R^(sum) is lower than R_(α=0) ^(sum). Herein, R_(α=0) ^(sum)denotes the system transmission rate (i.e., the system transmission rateobtained by the maximum throughput scheduling) achievable when α=0.There exists no simple inverse function for determining the value αusing {p_(i)}_(i=1, . . . , K), {x_(i) ^(eff)}_(i=1, . . . , K) andR^(sum) as the input variables in Equation 9. Accordingly, by applyingvarious values (e.g., 0, 0.1, . . . , 3.9, 4) to Equation 9, the value αwhich makes the values of the both sides of Equation 9 most alike (i.e.,minimizes the difference of the both side values) is selected.

After the value α is determined, the generalized PF scheduler sets theindividual weight value p_(i) of each terminal. As p_(i) increases, thecorresponding terminal is selected more frequently and the averagetransmission rate is raised. As p_(i) decreases, the terminal isselected less frequently and the average transmission rate is lowered.When p_(i) of one terminal is changed, it affects the averagetransmission rate of every other terminal. Thus, the present inventionprovides a method for regulating p_(i) to increase the transmission rateof the terminal having the very low average transmission rate while notchanging the system transmission capacity; that is, the averagetransmission rate sum of all of the terminals.

The increasing the transmission rate of the terminal having the lowaverage transmission rate while not changing the average transmissionrate sum of all of the terminals implies that the average transmissionrate of other terminals needs to decrease. Hence, when the averagetransmission rate of one terminal falls short of the averagetransmission rate required in the service and concurrently the averagetransmission rate of one terminal exceeds the required averagetransmission rate, an algorithm for giving the data transmissionopportunity of the terminal of the excess average transmission rate tothe terminal of the short average transmission rate is used. The averagetransmission rate of other terminals may be maintained. The suggestedalgorithm is now explained.

Assuming that N-ary terminals have the average transmission rate fallingshort of the average transmission rate required in the service, theconcurrent calculation of the solution p_(i) for increasing the averagetransmission rate of the N-ary terminals up to the required transmissionrate is subject to high computational complexity because it is tocalculate an optimal solution in an N-dimensional feasible solutionspace. Thus, the suggested algorithm selects one of the N-ary terminalshaving the average transmission rate falling short of the requiredtransmission rate and one of the terminals having the averagetransmission rate exceeding the required transmission rate, and thusdetermines the weight value p_(i) for giving the data transmissionopportunity of the terminal of the excess average transmission rate tothe terminal of the short average transmission rate. The weightdetermination for the two selected terminals is performed for N-arytimes per step, and thus the weight value p_(i) for the N-ary terminalsto satisfy their target transmission rate can be determined.

When the current average transmission rates of the terminals m and n areR_(m) and R_(n) respectively and {tilde over (R)}_(m) and {tilde over(R)}_(n) are the target average transmission rates, the current weightvalues p_(m) and p_(n) of the terminals m and n are changed to τ_(m) andτ_(n) based on Equation 10.

{tilde over (p)} _(m)=τ_(m) p _(m) , {tilde over (p)} _(n)=τ_(n) p_(n)  [Eqn. 10]

In Equation 10, τ_(m) and τ_(n) are obtained based on Equation 11.

$\begin{matrix}{{\tau_{m} = \left( \frac{{\overset{\sim}{R}}_{m}}{R_{m}} \right)^{\alpha}},{\tau_{n} = \left( \frac{{\overset{\sim}{R}}_{n}}{R_{n}} \right)^{\alpha}}} & \left\lbrack {{Eqn}.\mspace{14mu} 11} \right\rbrack\end{matrix}$

τ_(m) and τ_(n) satisfy a condition of Equation 12.

$\begin{matrix}{{0 \leq \tau_{n} \leq \left( {1 + {\left( \frac{p_{m}}{p_{n}} \right)^{1/\alpha}\left( \frac{x_{m}^{eff}}{x_{n}^{eff}} \right)^{{1/\alpha} - 1}}} \right)^{\alpha}},{\tau_{m} = \left( {1 + {\left( {1 - \tau_{n}^{1/\alpha}} \right)\left( \frac{p_{m}}{p_{n}} \right)^{1/\alpha}\left( \frac{x_{m}^{eff}}{x_{n}^{eff}} \right)^{{1/\alpha} - 1}}} \right)^{\alpha}}} & \left\lbrack {{Eqn}.\mspace{14mu} 12} \right\rbrack\end{matrix}$

In an embodiment, the PF scheduling with α=1 satisfies the simplecondition of Equation 13.

{tilde over (p)} _(m) +{tilde over (p)} _(n) =p _(m) +p _(n)  [Eqn. 13]

FIG. 4 is a flowchart of a terminal average transmission rate controlalgorithm according to an embodiment of the present invention.

Referring to FIG. 4, the scheduler determines the value α to use inblock 400. Since the value α affects the whole average transmission rateof the terminal, the fairness degree used in the wireless network isdefined and the value α is defined in accordance with the fairnessdegree. For example, the value α satisfying the system transmission ratewith the desired value R^(sum) and satisfying the maximum fairness canbe determined based on Equation 9.

In block 402, the scheduler initializes the weight value of eachterminal to 1; that is, defines {p_(i)}_(i=1, . . . , K)=1. Next, theweight value of each terminal is continuously updated to satisfy thetarget transmission rate.

In block 404, the scheduler estimates the average transmission rate ofeach terminal with the determined value α and the weight value{p_(i)}_(i=1, . . . , K)=1 of each terminal using the terminal averagetransmission rate estimation algorithm of FIG. 3.

In block 406, the scheduler determines whether the average transmissionrate of every terminal meets the target transmission rate by comparingthe estimated average transmission rate of each terminal with the targettransmission rate. When the average transmission rate of every terminalmeets the target transmission rate, the terminal selector of FIG. 1selects the terminals to send data using the current value α and theterminal weight value {p_(i)}_(i=1, . . . , K).

By contrast, when the average transmission rate of every terminal doesnot meet the target transmission rate, the scheduler regulates theterminal weight value {p_(i)}_(i=1, . . . , K) in blocks 410 through416.

In block 410, the scheduler selects the terminal m and the terminal n ofwhich the weight value is to change. The scheduler selects the terminalof the average transmission rate falling short of the targettransmission rate and the terminal of the average transmission rateexceeding the target transmission rate. This is to give the datatransmission opportunity of the terminal of the excess averagetransmission rate to the terminal of the short average transmissionrate.

In block 412, the scheduler calculates τ_(m) and τ_(n) using the ratioof the target transmission rate and the average transmission rate basedon Equation 11.

In block 414, the scheduler checks whether τ_(m) and τ_(n) calculated inblock 412 satisfies the condition of Equation 12. When the condition isnot satisfied, the scheduler repeats the blocks 410 and 412. When thecondition is satisfied, the scheduler goes to block 416.

In block 416, the scheduler changes the weight of the terminal m and theterminal n based on Equation 10. Next, the scheduler determines whetherevery terminal meets the target transmission rate in block 406. Thescheduler repeats the blocks 410 and 416 until every terminal satisfiesthe target transmission rate as much as possible.

In block 408, the scheduler selects the terminal to send data using thevalue α determined in block 400 and the terminal weight value{p_(i)}_(i=1, . . . , K) updated in blocks 410 through 416.

Performance Analysis of the Present Technique

The present invention provides the scheduling apparatus and method forcontrolling the fairness between the users and the average transmissionrate of each user in the downlink wireless communication systemincluding the MIMO antennas. To analyze the performance of the suggestedtechniques, system level simulation is conducted on MIMO mode 2 ofMobile WiMAX. The performance of the average transmission rateestimation and control algorithms of the present generalized PFscheduler is analyzed through the system level simulation results.

FIG. 5 depicts the average transmission rate of the terminals in theMIMO mode 2 system of WiMAX with 12 users distributed per sector. Thevalue α used in the generalized PF scheduler is assumed to be 1. Theresult “Before control” indicates the average transmission rate of theterminal when the weight value of every terminal is 1; that is, when[p₁,p₂,p₃, . . . , p₁₂]=[1,1,1, . . . , 1]. “Actual Throughput”indicates the actual average transmission rate of the terminals when theweight value of the terminal is changed to [{tilde over (p)}₁,{tildeover (p)}₂,{tilde over (p)}₃, . . . , {tilde over (p)}₁₂]=[0.5,1.5,1, .. . , 1]. “Estimated Throughput” indicates the average transmission rateresult of the terminal estimated by the present average transmissionrate estimation method when the weight value of the terminal is changedto [{tilde over (p)}₁,{tilde over (p)}₂,{tilde over (p)}₃, . . . ,{tilde over (p)}₁₂]=[0.5,1.5,1, . . . , 1]. According to the results ofFIG. 5, the estimated average transmission rate of the terminal 1 andthe terminal 2 has an error of only about 1.3% and approaches the targettransmission rate. The average transmission rate of the terminal 3through the terminal 12 of the unchanging weight does not change. Assuch, the average transmission rate prediction and control methods ofthe present generalized PF scheduler work quite accurately andeffectively in the actual system.

As set forth above, by calculating the average transmission rate withthe Gaussian distribution and determining the weight and the fairnesscoefficient to reach the target transmission rate, it is possible tocontrol the fairness between the terminals and to efficiently controlthe transmission rate of the terminals according to the requiredtransmission rate and the channel environment of the terminals.

While the invention has been shown and described with reference tocertain exemplary embodiments thereof, it will be understood by thoseskilled in the art that various changes in form and details may be madetherein without departing from the spirit and scope of the invention asdefined by the appended claims and their equivalents.

1. A scheduling method in a wireless communication, the methodcomprising: receiving a Channel Quality Indicator (CQI) from a pluralityof terminals; determining an average transmission rate of each terminalbased on the CQI by approximating an instantaneous transmission ratedistribution to a Gaussian distribution; determining a weight of eachterminal such that the average transmission rate of each terminalsatisfies a target transmission rate; and selecting a terminal set byapplying the determined weight.
 2. The scheduling method of claim 1,wherein the determining of the average transmission rate of eachterminal by approximating the instantaneous transmission ratedistribution to the Gaussian distribution comprises: determining theinstantaneous transmission rate distribution by converting the CQI tothe instantaneous transmission rate with respect to each terminal;approximating the instantaneous transmission rate distribution to theGaussian distribution; and determining the average transmission rateusing the instantaneous transmission rate approximated to the Gaussiandistribution.
 3. The scheduling method of claim 2, wherein theinstantaneous transmission rate approximated to the Gaussiandistribution is expressed as the following equation:x _(i) ^(eff) =m _(i)+ε_(i)σ_(i) where an average and a standarddeviation when the instantaneous transmission rate distributionreceivable by an i-th terminal is approximated to the Gaussiandistribution are defined as m_(i) and σ_(i) respectively, and ε_(i) is areal value determined according to the number of users.
 4. Thescheduling method of claim 3, wherein ε_(i) is calculated based on thefollowing equation: ε_(i)≈ε(K)=K∫ _(x=0) ^(∞) xf _((0,1))(x)(F_((0,1))(x))^(K-1) dx where f_((0,1)) and F_((0,1)) denote a ProbabilityDistribution Function (PDF) and a Cumulative Distribution Function (CDF)of a standard normal distribution.
 5. The scheduling method of claim 2,wherein the average transmission rate is calculated based on thefollowing equation:$R_{i} = \frac{\left( {p_{i}x_{i}^{eff}} \right)^{1/\alpha}}{\sum\limits_{k = 1}^{K}\frac{\left( {p_{k}x_{k}^{eff}} \right)^{1/\alpha}}{x_{k}^{eff}}}$where R_(i) denotes the average transmission rate, p_(i) denotes theweight of the terminal i x_(i) ^(eff) denotes the instantaneoustransmission rate approximated to the Gaussian distribution for theterminal i, and α denotes a parameter for regulating fairness.
 6. Thescheduling method of claim 1, wherein the determining of the weight ofeach terminal such that the average transmission rate of each terminalsatisfies the target transmission rate comprises: determining a fairnesscoefficient α and initializing the weight of each terminal; determiningwhether the average transmission rate of every terminal satisfies thetarget transmission rate by comparing the determined averagetransmission rate of each terminal with the target transmission rate;when the average transmission rate of every terminal does not satisfythe target transmission rate, selecting at least two terminals; anddetermining the weight to lower the average transmission rate of atleast one first terminal of the at least two selected terminals and toraise the average transmission rate of other second terminals.
 7. Thescheduling method of claim 6, wherein the fairness coefficient α is avalue satisfying the target transmission rate R^(sum) and maximumfairness, and is determined based on the following equation:$R^{sum} = {\sum\limits_{i = 1}^{K}{\left( {p_{i}x_{i}^{eff}} \right)^{1/\alpha}/{\sum\limits_{k = 1}^{K}\frac{\left( {p_{k}x_{k}^{eff}} \right)^{1/\alpha}}{x_{k}^{eff}}}}}$where R^(sum) denotes the target transmission rate, p_(i) denotes theweight of the terminal i, x_(i) ^(eff) denotes the instantaneoustransmission rate approximated to the Gaussian distribution for theterminal i, and α denotes a parameter for regulating fairness.
 8. Thescheduling method of claim 6, wherein the selecting of the at least twoterminals when the average transmission rate of every terminal does notsatisfy the target transmission rate, selects at least one terminal ofwhich the average transmission rate falls short of the targettransmission rate and at least one terminal of which the averagetransmission rate exceeds the target transmission rate.
 9. Thescheduling method of claim 6, wherein, when two terminals m and n areselected, weights τ_(m) and τ_(n) are determined based on the followingequation:${\tau_{m} = \left( \frac{{\overset{\sim}{R}}_{m}}{R_{m}} \right)^{\alpha}},{\tau_{n} = \left( \frac{{\overset{\sim}{R}}_{n}}{R_{n}} \right)^{\alpha}}$where R_(m) and R_(n) denote a current average transmission rate of theterminals m and n, {tilde over (R)}_(m) and {tilde over (R)}_(n) denotetarget average transmission rates, and α denotes a parameter forregulating fairness.
 10. The scheduling method of claim 6, wherein, whentwo terminals m and n are selected, the determined weight satisfies thefollowing equation:${0 \leq \tau_{n} \leq \left( {1 + {\left( \frac{p_{m}}{p_{n}} \right)^{1/\alpha}\left( \frac{x_{m}^{eff}}{x_{n}^{eff}} \right)^{{1/\alpha} - 1}}} \right)^{\alpha}},{\tau_{m} = \left( {1 + {\left( {1 - \tau_{n}^{1/\alpha}} \right)\left( \frac{p_{m}}{p_{n}} \right)^{1/\alpha}\left( \frac{x_{m}^{eff}}{x_{n}^{eff}} \right)^{{1/\alpha} - 1}}} \right)^{\alpha}}$where p_(m) and p_(n) denote an initial weight of the terminal m and theterminal n, x_(m) ^(eff) and x_(n) ^(elf) denote the instantaneoustransmission rate approximated to the Gaussian distribution for theterminal m and the terminal n, and α denotes a parameter for regulatingfairness.
 11. The scheduling method of claim 1, wherein the selecting ofthe terminal set is based on a generalized Proportional Fair (PF)algorithm of the following equation:${O_{S}\lbrack n\rbrack} = {\underset{O}{\arg \; \max}{\sum\limits_{i \in O}\left\{ {p_{i}\frac{r_{i}\lbrack n\rbrack}{\left( {R_{i}\left\lbrack {n - 1} \right\rbrack} \right)^{\alpha}}} \right\}}}$where O denotes all feasible subsets for K-ary terminals wanting to senddata, O_(S)[n] denotes a terminal set selected by a scheduler S toservice in an n-th time slot, p_(i) denotes the weight of the terminali, α denotes a parameter for regulating fairness, R_(i)[n] denotes theaverage transmission rate of the i-th terminal, and r_(i)[n] denotes theinstantaneous transmission rate of the i-th terminal transmittable inthe n-th time slot.
 12. A scheduling apparatus in a wirelesscommunication comprising: a receiver configured to receive a ChannelQuality Indicator (CQI) from a plurality of terminals; an averagetransmission rate determiner configured to determine an averagetransmission rate of each terminal based on the CQI by approximating aninstantaneous transmission rate distribution to a Gaussian distribution;an average transmission rate controller configured to determine a weightof each terminal such that the average transmission rate of eachterminal satisfies a target transmission rate; and a terminal selectorconfigured to select a terminal set by applying the determined weight.13. The scheduling apparatus of claim 12, wherein the averagetransmission rate determiner determines the instantaneous transmissionrate distribution by converting the CQI to the instantaneoustransmission rate with respect to each terminal, approximates theinstantaneous transmission rate distribution to the Gaussiandistribution, and determines the average transmission rate using theinstantaneous transmission rate approximated to the Gaussiandistribution.
 14. The scheduling apparatus of claim 13, wherein theinstantaneous transmission rate approximated to the Gaussiandistribution is expressed as the following equation:x _(i) ^(eff) =m _(i)+ε_(i)σ_(i) where an average and a standarddeviation when the instantaneous transmission rate distributionreceivable by an i-th terminal is approximated to the Gaussiandistribution are defined as m_(i) and σ_(j) respectively, and ε_(i) is areal value determined according to the number of users.
 15. Thescheduling apparatus of claim 14, wherein ε_(i) is calculated based onthe following equation:ε_(i)≈ε(K)=K∫ _(x=0) ^(∞) xf _((0,1))(x)(F _((0,1))(x))^(K-1) dx wheref_((0,1)) and F_((0,1)) denote a Probability Distribution Function (PDF)and a Cumulative Distribution Function (CDF) of a standard normaldistribution.
 16. The scheduling apparatus of claim 13, wherein theaverage transmission rate is calculated based on the following equation:$R_{i} = \frac{\left( {p_{i}x_{i}^{eff}} \right)^{1/\alpha}}{\sum\limits_{k = 1}^{K}\frac{\left( {p_{k}x_{k}^{eff}} \right)^{1/\alpha}}{x_{k}^{eff}}}$where R_(i) denotes the average transmission rate, p_(i) denotes theweight of the terminal i, x_(i) ^(eff) denotes the instantaneoustransmission rate approximated to the Gaussian distribution for theterminal i, and α denotes a parameter for regulating fairness.
 17. Thescheduling apparatus of claim 12, wherein the average transmission ratecontroller determines a fairness coefficient α, initializes the weightof each terminal, determines whether the average transmission rate ofevery terminal satisfies the target transmission rate by comparing thedetermined average transmission rate of each terminal with the targettransmission rate, selects at least two terminals when the averagetransmission rate of every terminal does not satisfy the targettransmission rate, and determines the weight to lower the averagetransmission rate of at least one first terminal of the at least twoselected terminals and to raise the average transmission rate of othersecond terminals.
 18. The scheduling apparatus of claim 17, wherein thefairness coefficient α is a value satisfying the target transmissionrate R^(sum) and maximum fairness, and is determined based on thefollowing equation:$R^{sum} = {\sum\limits_{i = 1}^{K}{\left( {p_{i}x_{i}^{eff}} \right)^{1/\alpha}/{\sum\limits_{k = 1}^{K}\frac{\left( {p_{k}x_{k}^{eff}} \right)^{1/\alpha}}{x_{k}^{eff}}}}}$where R^(sum) denotes the target transmission rate, p_(i) denotes theweight of the terminal i, x_(i) ^(eff) denotes the instantaneoustransmission rate approximated to the Gaussian distribution for theterminal i, and α denotes a parameter for regulating fairness.
 19. Thescheduling apparatus of claim 17, wherein the average transmission ratecontroller selects at least one terminal of which the averagetransmission rate falls short of the target transmission rate and atleast one terminal of which the average transmission rate exceeds thetarget transmission rate.
 20. The scheduling apparatus of claim 17,wherein, when two terminals m and n are selected, weights τ_(m) andτ_(n) are determined based on the following equation:${\tau_{m} = \left( \frac{{\overset{\sim}{R}}_{m}}{R_{m}} \right)^{\alpha}},{\tau_{n} = \left( \frac{{\overset{\sim}{R}}_{n}}{R_{n}} \right)^{\alpha}}$where R_(m) and R_(n) denote a current average transmission rate of theterminals m and n, {tilde over (R)}_(m) and {tilde over (R)}_(n) denotetarget average transmission rates, and α denotes a parameter forregulating fairness.
 21. The scheduling apparatus of claim 17, wherein,when two terminals m and n are selected, the determined weight satisfiesthe following equation:${0 \leq \tau_{n} \leq \left( {1 + {\left( \frac{p_{m}}{p_{n}} \right)^{1/\alpha}\left( \frac{x_{m}^{eff}}{x_{n}^{eff}} \right)^{{1/\alpha} - 1}}} \right)^{\alpha}},{\tau_{m} = \left( {1 + {\left( {1 - \tau_{n}^{1/\alpha}} \right)\left( \frac{p_{m}}{p_{n}} \right)^{1/\alpha}\left( \frac{x_{m}^{eff}}{x_{n}^{eff}} \right)^{{1/\alpha} - 1}}} \right)^{\alpha}}$where p_(m) and p_(n) denote an initial weight of the terminal m and theterminal n, x_(m) ^(eff) and x_(n) ^(eff) denote the instantaneoustransmission rate approximated to the Gaussian distribution for theterminal m and the terminal n, and α denotes a parameter for regulatingfairness.
 22. The scheduling apparatus of claim 12, wherein the terminalselector performs a Proportional Fair (FT) scheduling algorithm based ona generalized PF algorithm of the following equation:${O_{S}\lbrack n\rbrack} = {\underset{O}{\arg \; \max}{\sum\limits_{i \in O}\left\{ {p_{i}\frac{r_{i}\lbrack n\rbrack}{\left( {R_{i}\left\lbrack {n - 1} \right\rbrack} \right)^{\alpha}}} \right\}}}$where O denotes all feasible subsets for K-ary terminals wanting to senddata, O_(S)[n] denotes a terminal set selected by a scheduler S toservice in an n-th time slot, p_(i) denotes the weight of the terminali, α denotes a parameter for regulating fairness, R_(i)[n] denotes theaverage transmission rate of the i-th terminal, and r_(i)[n] denotes theinstantaneous transmission rate of the i-th terminal transmittable inthe n-th time slot.